Accelerating Photonic Integrated Circuit Design: Traditional, ML and Quantum Methods

• URL: http://arxiv.org/abs/2506.18435v2
• Date: Thu, 03 Jul 2025 10:56:38 GMT
• Title: Accelerating Photonic Integrated Circuit Design: Traditional, ML and Quantum Methods
• Authors: Alessandro Daniele Genuardi Oquendo, Ali Nadir, Tigers Jonuzi, Siddhartha Patra, Nilotpal Kanti Sinha, Román Orús, Sam Mugel,
• Abstract summary: Photonic Integrated Circuits (PICs) provide superior speed, bandwidth, and energy efficiency.<n>Despite their potential, PIC design and integration lag behind those in electronics, calling for groundbreaking advancements.<n>This review outlines the state of PIC design, comparing traditional simulation methods with machine learning approaches.
• Score: 36.136619420474766
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Photonic Integrated Circuits (PICs) provide superior speed, bandwidth, and energy efficiency, making them ideal for communication, sensing, and quantum computing applications. Despite their potential, PIC design workflows and integration lag behind those in electronics, calling for groundbreaking advancements. This review outlines the state of PIC design, comparing traditional simulation methods with machine learning approaches that enhance scalability and efficiency. It also explores the promise of quantum algorithms and quantum-inspired methods to address design challenges.

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